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The Hierarchical Fuzzy Evaluation System and Its Application

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Advances in Machine Learning and Cybernetics

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3930))

Abstract

The hierarchical fuzzy evaluation system (HFES) and its application in intelligent workflow management system (IWfMS) are discussed in this paper. First, the definition of HFES is discussed, including the definitions of the evaluation items and the relationships among them, based on the five common operations. Second, the running algorithms of the HFES are introduced to compute the values of those evaluation items and the result of the HFES. Subsequently, the application of the HFES in the IWfMS is presented in detail including the cooperating model. The experiments are carried out and the results show that the HFES is effective.

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Authors and Affiliations

  1. School of Economics and Management, Southwest Jiaotong University, Chengdu, (610031), Sichuan, P.R. China

    Xiaoping Qiu & Ming Jian

  2. Intelligent Control Development Center, Southwest Jiaotong University, Chengdu, (610031), Sichuan, P.R. China

    Xiaoping Qiu, Yang Xu & Haiming Li

  3. School of Information and Engineering, Zhejiang Forestry University, Lin’an, Hangzhou, (311300), Zhejiang, P.R. China

    Haiming Li

Authors
  1. Xiaoping Qiu
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  2. Yang Xu
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  3. Ming Jian
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  4. Haiming Li
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Editor information

Editors and Affiliations

  1. Department of Computing, Hong Kong Polytechnic University, P.O. Box, Hong Kong, China

    Daniel S. Yeung

  2. School of Creative Media, City University of Hong Kong,, China

    Zhi-Qiang Liu

  3. Department of Mathematics and Computer Science, Hebei University, 071002, Baoding, Hebei, P.R. China

    Xi-Zhao Wang

  4. School of Electrical and Information Engineering, University of Sydney, 2006, NSW, Australia

    Hong Yan

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© 2006 Springer-Verlag Berlin Heidelberg

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Qiu, X., Xu, Y., Jian, M., Li, H. (2006). The Hierarchical Fuzzy Evaluation System and Its Application. In: Yeung, D.S., Liu, ZQ., Wang, XZ., Yan, H. (eds) Advances in Machine Learning and Cybernetics. Lecture Notes in Computer Science(), vol 3930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11739685_43

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  • DOI: https://doi.org/10.1007/11739685_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33584-9

  • Online ISBN: 978-3-540-33585-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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